Data science is a broad scientific field in which training in statistics, math, programming, AI, machine learning, and advanced analytics provide organizations with actionable insights based on their data. These professionals must often handle huge quantities of raw data to reach useful conclusions. The insights found through data science are essential for helping companies formulate strategic plans and make decisions moving forward.
The term “data science” was first used in the 1960s by John Tukey, a mathematician focused on analyzing data. However, it wasn’t until decades later that this field transformed to encapsulate the growing need to gather and process huge amounts of data. At this time, new techniques were needed to perform data analysis. Today, Data Scientists are hired to work in a variety of areas such as creating machine learning algorithms, performing research for academic journals, or offering suggestions intended to improve business strategy. In 2022, Glassdoor listed data science as one of the top 50 job paths in the U.S. In the time since, the field has continued to expand, as companies rely more on analytics to fuel their innovations and revenue.
What Can You Do with Data Science Training?
The US Bureau of Labor Statistics estimates that the field of data science will grow by a whopping 35% from 2022 to 2032, which is well above the national average in other fields. Because data science training is necessary in nearly all private and public sectors, those who have experience in this field have many high-paying career options. Knowledge of data science has applications in retail, business analytics, machine learning, web development, finance, and health-related professions. In addition to opening many professional doors, another reason people choose to learn data science is because it can have positive impacts on society at large. Data Scientists are hired to solve challenges, propose innovations, and drive change. The results of their analysis not only help their organization perform better but also can have real-world impacts that lead to sustainable development and progress around the globe. As more emerging technologies like AI, big data, and the Internet of Things are integrated into the field of data science, this field is expected to continue to evolve and transform how we harness and leverage data for everyday purposes.
In addition to its myriad professional uses, data science also has applications for non-professionals. Data science knowledge can be used to create targeted product advertising, speech recognition, travel route optimization, and medical imaging analysis. It is also a useful tool for providing insights into customer purchasing behavior and preferences, as well as deciding what to wear each morning after checking the weather report.
What Will I Learn in a Data Science Class?
Enrolling in a data science course is an excellent way to receive hands-on training in a range of useful skills. Although the content of each program varies depending on the provider and course focus, there are several core skills you can expect to encounter during your training.
Computer Programming
Most data science classes instruct learners on one or more computer programming languages. Participants often explore Python and how it can be used to prepare and clean data so it’s ready to analyze, automate repetitive tasks like aggregating, formatting, and updating data, and work with its data science libraries. Some courses also teach participants how to use SQL to query databases and retrieve useful information.
Dashboards & Visualizations
Data science training often teaches students how to visualize information and present it as dashboards or other types of data visualizations. Participants often work with tools like Tableau and Excel to analyze and visualize data. They also explore how to use Python’s dashboard and plotting libraries like Seaborn, Dash Enterprise, Matplotlib, or Plotly. This ensures that various audience members can access and understand the information they uncover during the analytics process.
Machine Learning Models
Machine Learning models are computer programs that use algorithms to learn from data and offer predictions. These models can locate patterns or offer decisions based on datasets that were previously unseen. Coursework in data science usually prepares participants to work with the data they have to create machine learning models and then study how they’re performing. They may also work with Python libraries like Pandas to clean and balance data and scikit-learn to solve problems. By the end of training, students should be able to analyze data results to locate places to improve.
Critical Thinking
In addition to providing participants with technical training in skills like data visualization, machine learning, and computer programming, data science classes also help students develop their capacity for critical thinking. The training they receive can help them formulate hypotheses better, analyze questions, and objectively evaluate results. To do so, students must have a solid understanding of how to utilize any available resources and evaluate the problem from various angles. Learners will also be able to spot opportunities and propose solutions to problems.
How Hard is It to Learn Data Science?
Since many data science careers require a range of technical requirements, this field can pose challenges for some learners to study, especially when compared to other tech fields. Data science is a broad field that requires knowledge of several applications and programming languages such as Python, SQL, R, Tableau, Power BI, and Excel, as well as skills like data analysis and machine learning. Acquiring this vast body of knowledge is challenging for some, especially those who are new to working with big data. Those who already have familiarity with one or more of these tools may find it much easier and faster than those who have to start from scratch. Additionally, students who are interested in acquiring a basic understanding of data science will typically find that it is much easier to acquire than advanced-level data science training, which is essential for professional Data Scientists.
Because data science knowledge has many applications, each learner approaches the data science learning process differently. Some study Python programming as part of a more robust certificate program. Others may instead focus on learning R or Python only because they are studying back-end web development. One of the most challenging aspects of studying this field is learning it in-depth, which can take many months or longer. One of the most effective ways to gain hands-on training in the tools and applications needed to become a Data Scientist is to enroll in a live course like a bootcamp or certificate program that offers small class instruction for learners at all levels.
What Are the Most Challenging Parts of Learning Data Science?
All learners differ in terms of the challenges they encounter when studying data science. For many, the inherent challenges of this field pertain to learning industry-specific tools, hard and soft skills, and keeping up with constant innovations.
During the past decade, the field of data science has rapidly transformed as tools like AI, deep learning, and machine learning become more prevalent. Some learners may struggle to keep up with the sheer pace of innovations. Additionally, because data science is a staple in so many industries, the tools required to work in a particular field may differ greatly from one professional setting to another. For example, data science professionals who are employed in retail or healthcare will require knowledge of different tools than those who work in marketing or finance. Some industries may require job applicants to have Tableau training, whereas others may prefer Power BI.
Another common challenge when learning data science is how best to handle data and evaluate its quality. Data Scientists must be skilled at data mining and able to interpret data findings and communicate them to relevant stakeholders. Some individuals may also struggle to ensure the data they’re using is of the highest quality. Working with low-quality data can lead to incomplete or even inaccurate results that prevent the Data Scientist from reaching useful conclusions.
How Long Does It Take to Learn Data Science?
The amount of time it takes the average person to learn data science varies, depending on their ultimate goals for using this skill-set, as well as the knowledge they bring into the process. For most, the data science learning process poses challenges, in part because of how in-depth it is. Most experts estimate that it takes learners between six months and a full year to master basic data science concepts and practices. Acquiring expertise in this field can take years, especially for those who hope to apply their knowledge to their job.
Should I Learn Data Science in Person or Online?
Deciding whether to study data science in-person in Orlando or through online coursework is an important choice all learners will need to make. Each training format has its unique advantages and drawbacks that should be weighed.
For most students, studying data science through in-person training is the most effective and hands-on way to fully learn this topic. Those who study in-person in Orlando have access to the most up-to-date software and tools already installed on the computers at the training facility. Live coursework also provides the opportunity for students to ask questions in real-time and receive immediate clarification and support. Individuals who attend class live online can even give the instructor permission to share their screen for additional assistance. Live classes are also a great way for those studying data science to connect with other students and benefit from the supportive educational community as they study.
Enrolling in an in-person data science class requires that students commute to and from the training facility for regularly scheduled classes. Those who lack reliable transportation or live far from a training center may, therefore, find this type of coursework prohibitive. Students who opt for live online classes complete all coursework remotely using Zoom or another teleconferencing platform. Although they won’t need to commute for their studies, they will need to be able to commit to attending regularly scheduled class meetings. For those who have full-time work schedules, this may pose challenges.
The most flexible training format for data science study is on-demand coursework. Unlike live training, which takes place in real-time with a live instructor, on-demand classes are recorded at an earlier time and placed online for students to access at their convenience. Learners have the freedom to determine their own learning speed. They can pause, rewind, and even rewatch entire lessons as necessary to ensure they’re retaining the content. Cost is a major incentive for this type of instructor. Whereas live courses can cost hundreds or even thousands of dollars, self-paced study options are typically a much more affordable training option. Learners who choose this type of coursework should keep in mind that they will not have real-time access to an instructor, though, since the content is pre-recorded. Those just getting started with data science or who are looking to master it for professional reasons may struggle to learn advanced concepts through on-demand content because they will be on their own to find answers to questions.
Can I Learn Data Science for Free Online?
If you want to learn data science but don’t want to invest in a formal class, the good news is that there are plenty of free online resources and tutorials in data science that can help you get started:
- Noble Desktop’s data science blog is a great resource for learning more about data science. More than 100 articles are available on various data science topics, including how to use this field in marketing and advertising and the elite programming languages for data science. Noble also has a learn data science page that provides learners with links to free seminars and video tutorials on topics ranging from data visualization to Python coding.
- Free online books and other publications are also available from some publishers via PDF or eBook.
- Industry news can be another excellent free resource. Data Science Central, the Twoard Data Science blog (hosted by Medium), or Google News are just a few free news sources with relevant data science information.
- Some of the most well-known names in data science are the largest tech names around the globe. Companies like Google, Amazon, and Microsoft all feature data analytics or data science news stories or feeds that offer useful information.
While free online data science resources can be a great way to learn the basics of this in-demand field and find specific answers to data science-related questions, most learners will require a more structured learning approach if they want to master this skill set for professional development purposes.
What Should I Learn Alongside Data Science?
Because data science is a broad field, there are many skills and tools that are related to data science that some learners may wish to learn simultaneously. The decision of which tools is ultimately up to each learner and will depend on what they hope to use their data science training for, as well as their industry of focus. Some individuals may find that it’s useful to study open-source programming languages like R and Python, which are good for beginners and also are able to handle large amounts of data. Other individuals may opt to work with languages like VBA, Julia, JavaScript, or SQL. Often, data science training programs include instruction in at least one computer programming language.
Some individuals may want to learn more about deep learning and machine learning alongside their data science studies. These models are used for data mining. Additionally, knowledge of data wrangling, or cleaning and organizing complicated datasets, is another useful skill some may want to pick up during their training. Finally, since Data Scientists commonly work with cloud computing tools for data analysis and visualization, it can be useful to study cloud computing to learn how to work with the information stored in popular cloud platforms.
Industries That Use Data Science
Data science has applications in many industries and professions. Those with data science knowledge can use it in Orlando to help their organizations prepare data, better understand customers, and improve overall operations. Read on to learn more about the role data science plays in finance, retail, healthcare, and nonprofits.
Finance
Finance is another key sector of Orlando’s economy. The city has a vast talent pool in finance, with more than 60,000 people employed in fields like loans, financial services, and software development. Many top financial service companies are also located in the Orlando area, including mortgage brokers and accounting firms like International Assets Advisory and CNL Financial Group. Many financial institutions are drawn to Florida because of the state’s 5.5% corporate tax rate.
Within the finance sector in Orlando, data science training is useful because it can help banks incorporate techniques and practices designed to provide customers with improved support and services. Financial data science is used to analyze customer spending patterns, detect fraud, automate pricing, and manage risk. Data Scientists employed in the finance sector use data modeling techniques to make structured and semi-structured data cohesive. They also use natural language processing to analyze this information. One of the main applications of financial data science is in designing and coding new algorithms that help manage data analytics and machine learning processes.
Retail
Another prominent Orlando industry is retail. Those who work in the city’s retail sector cater to a growing population with high spending patterns, as well as a constant flow of visitors. The city’s customer spending is largely driven by those who visit its popular theme parks like Disney World. Retail trade jobs in Orlando employ over five times more people in the city than the national average in other locations. Those employed in Orlando’s retail industry use their training to predict customer spending patterns so they can stock merchandise accordingly. They also use data analytics to improve customer satisfaction rates and ensure that they have a personalized shopping experience. Since this industry is customer-focused, catering to customers through data insights is a great way for Retailers to retain a competitive edge and apply predictive techniques that will continue to gain their business.
Healthcare
Orlando is well-known for its state-of-the-art research and education facilities. Large health systems such as Orlando Health and AdventHealth, are headquartered in Orlando. Additionally, six of the 50 largest hospitals in the US are located within a two-hour drive of Orlando. Over 195,000 people are employed in the city’s healthcare and life science sector. Those who have data science training can put their skills to use in Orlando structuring and managing large stores of data. They can also help healthcare providers create new strategies and policies aimed at improving the quality of healthcare services. Healthcare analytics also is a useful tool for customizing prescriptions and care, diagnosing diseases, and improving how hospitals operate.
Nonprofits
The state of Florida employs over 450,000 people in the nonprofit sector. There are nearly 1,600 nonprofits located in Orlando alone. Large organizations like Orlando Health, Adventists Health SystemsSunbelt, and Orlando Health Medical Group are among the major nonprofits located in this area. Data science knowledge is useful in the nonprofit sector because it can help organizations analyze their data to unearth insights pertaining to how effective their programs are, as well as donors and beneficiaries. This can help them make more data-driven decisions pertaining to improving fundraising strategies, maximizing their social media impact, and allocating resources.
Data Science Job Titles and Salaries
Data science training is an in-demand skill set in many careers in Orlando, including those in data engineering, data science, machine learning, and data modeling. Read on to find out more about the career paths available to those with data science skills and the salary ranges for each professional path.
Data Engineer
Data Engineers are hired to gather, manage, and convert raw data into a form that Business Analysts and Data Scientists can work with to unearth important insights. They create systems capable of collecting and storing these data and then analyzing them at scale. On a daily basis, Data Engineers perform tasks like creating algorithms to transform data, developing new validation methods and data analysis tools, and corresponding with management to articulate their organization’s objectives. In Orlando, Data Engineers earn $110,000-$120,000 annually.
Data Scientist
Those hired to work as Data Scientists in Orlando collect, sort through, and analyze vast datasets. The analysis they provide for their organization is integral to its decision-making process. Data Scientists also perform tasks like studying data trends and communicating their findings to pertinent stakeholders. They work with models and algorithms intended to make it easier to mine datasets to find support for their recommendations. The average salary for an Orlando-based Data Scientist is $142,000-$152,000 a year.
Machine Learning Engineer
In Orlando, Machine Learning Engineers handle large datasets and work to create machine learning systems capable of offering predictions. Machine learning is a type of artificial intelligence, which means those who work in this field must stay current on the latest AI trends, as well as programming languages like C and Python. On a daily basis, Machine Learning Engineers perform research on data, convert data science prototypes, and work with statistical analysis to improve the machine learning models they create. The average annual salary for a Machine Learning Engineer in Orlando is $140,000-$150,000.
Data Modeler
Data Modelers work with Data Architects and Database Administrators to create computer databases that organize data in a manner so that organizations can accomplish their goals. This career path requires training in database administration, SQL, software development, and data modeling. The average pay rate for Data Modelers in the Orlando area is $161,000-$171,000 a year.
Data Science Classes Near Me
If you want to learn data science but aren’t sure how to find classes, Noble Desktop’s Classes Near Me tool can help you find data science classes in Orlando.
Noble Desktop, an educator based in New York City, offers several live online data science classes for Orlando residents to take live online. The Data Science & AI Certificate is intended for those looking to pursue entry-level Python engineering or data science positions with their training. This beginner-friendly program begins by teaching students the basics of Python programming and how to use its science libraries for data analysis. Participants also explore how to create machine learning models and study their performance. Learners create data visualizations like dashboards and deploy these projects online using GitHub. All participants receive six 1-on-1 mentoring sessions as well. Registration for this class includes enrollment in Noble’s Python for AI: Create AI Apps with Flask & OpenAI at no additional cost.
Noble also has a Python Machine Learning Bootcamp for those interested in focusing their studies on this popular coding language. Students begin by studying logistic and linear regression. They then learn algorithms like random forests and decision trees. Participants receive instruction on how to use machine learning algorithms to solve real-world problems. The mathematical foundations for machine learning algorithms will be visually explained to students, which does not require formal math training. However, participants should know how to work with Python and its data science libraries as a prerequisite to enrolling. All Noble classes include a free course retake for up to a year.
General Assembly offers a Data Science Bootcamp for those interested in learning how to work with data to solve real-world problems. Those enrolled in this rigorous, intermediate-level program explore concepts like how to make ethical decisions using industry-standard tools like Tableau, Excel, SQL, Python, and Power BI. General Assembly also has a Data Science Short Course that prepares participants to use Python and statistics to create predictive models. This class is intended to prepare participants to use their training in real-world job settings that involve machine learning problems. These courses are both available in-person in Orlando and live online.
Those who want to focus their data science training on SQL can do so in Certstaffix Training’s SQL Querying—Advanced. This one-day program teaches students how to create advanced SQL queries, work with WHERE clauses, and make advanced joining tables. This provider also offers MySQL Workbench: Data Modeling & Development. In this comprehensive workshop, participants learn how to reverse engineer a database, manage its security, and use the MySQL Workbench to design and maintain MySQL databases. Both of these classes are taught live online; students can complete training remotely or use the computer lab that’s available in Winter Park, FL.
Learners in the Orlando area can also receive comprehensive data science training by enrolling in UCF Boot Camps Data Analytics and Visualization Book Camp. In this part-time class, students gain a comprehensive overview of how to analyze and visualize data. Coursework covers how to work with Tableau, SQL, Python, JavaScript, and Git/GitHub. By course completion, those enrolled will be familiar with MySQL, Matplotlib, NumPy, and pivot tables, as well as machine learning and Hadoop. This beginner-level class is taught in-person in Orlando.
Data Science Corporate Training
Would those at your workplace benefit from learning data science? If so, let Noble Desktop provide them with training. Noble has corporate and onsite data science training options for employees who are new to working with big data, as well as those who already have prior experience and want to take their skills further. Noble can come directly to your location in Orlando or provide live online course options via Zoom.
Instruction is available in core data science skills and tools, including programming languages like SQL and Python, artificial intelligence, and machine learning. Depending on your organization’s needs, Noble can train some or all of your employees in this in-demand skill set. You can also purchase bulk vouchers for Noble’s regularly offered classes at a discounted price. Coursework can also be customized to ensure your employees will get the most out of their training.
To find out more about the exciting training options available in data science, please don’t hesitate to contact Noble today.
